How do genetics, sex, and immune signaling shape bone health as mice age?
Our study shows that photon-counting CT in APOE mouse models reveals strong sex- and immune-dependent bone loss, with female HN mice showing the most pronounced decline.
Nadkarni, R.; Han, Z.Y.; Allphin, A.J.; Clark, D.P.; Badea, A.; Badea, C.T.
Photon-Counting Micro-CT for Bone Morphometry in Murine Models.
Tomography 2025, 11, 127. https://doi.org/10.3390/tomography11110127
Delighted to host Dr. Kristina Bliznakova, Fulbright Scholar, at Duke’s Quantitative Imaging & Analysis Lab. Looking forward to teaming up on photon-counting CT and virtual imaging.
New article and three institutions collaborating!
We identify network biomarkers of Alzheimer’s risk by combining high-res MRI with multifactorial analysis in ApoE mouse models. Joint volume + texture patterns reveal how genotype, sex, diet, & immunity interact to shape brain networks.
Bridgeford EW, Chung J, Anderson RJ, Mahzarnia A, Stout JA, Moon HS, Han ZY, Vogelstein JT, Badea A : Network biomarkers of Alzheimer’s disease risk derived from joint volume and texture covariance patterns in mouse models. PLoS One 20(8): e0327118. https://doi.org/10.1371/journal.pone.0327118
Our team developed anatomically variable digital Wistar rat phantoms for realistic preclinical imaging simulations, enabling PCCT studies & reducing animal use.
Segars, H. E., Nadkarni, R., Badea, C. T., Badea, A., Chin, B., Johnson, G. A., Payne, J., Samei, E., & Segars, W. P. (2025). Development of anatomically variable digital Wistar rat phantoms for small animal imaging research. Medical Physics, 52(8), e18057. https://doi.org/10.1002/mp.18057
Could your sense of smell reveal Alzheimer’s risk years before memory loss?
Our new study connects olfactory behavior, brain networks, & blood gene signatures to early AD vulnerability.
Moon, H.S.; Han, Z.Y.; Anderson, R.J.; Mahzarnia, A.; Stout, J.A.; Niculescu, A.R.; Tremblay, J.T.; Badea, A. Olfactory-Guided Behavior Uncovers Imaging and Molecular Signatures of Alzheimer’s Disease Risk. Brain Sci.2025, 15, 863. https://doi.org/10.3390/brainsci15080863
We developed a data-adaptive, self-supervised deep learning method combining sparse coding (SC) + visual transformer (ViT) for denoising pediatric cardiac photon-counting CT. Preserves anatomy, adapts to noise, generalizes well—even to preclinical data.
Clark, D. P., Cao, J. Y., & Badea, C. T. (2025). Denoising pediatric cardiac photon-counting CT data with sparse coding and data-adaptive, self-supervised deep learning. Medical Physics. https://doi.org/10.1002/mp.17918
Our team developed a CT-visible bioprinted vascular patch using dual-contrast bioinks. Photon-counting CT enabled precise tracking of structure and perfusion, highlighting the role of imaging in cardiac repair.
Gil, C. J., Allphin, A. J., Jin, L., Salar Amoli, M., Rezapourdamanab, S., Tomov, M. L., Hwang, B., Sridhar, V., El Shammas, L. R., Wu, Y., Evans, C. J., Li, L., Singh, Y., Nandwani, R. K., Nish, J., Shen, M., Mahmoudi, M., Bauser, H. D., Pourmorteza, A., Roeder, R. K., Badea, C. T., & Serpooshan, V. (2025). Image-guided cardiac regeneration via a 3D bioprinted vascular patch with built-in CT visibility. Chemical Engineering Journal, 475, 165926. https://doi.org/10.1016/j.cej.2025.165926
Our QIAL lab member Rohan Nadkarni brought the heat at the BME retreat—taking 2nd place in the rapid-fire challenge with original rap lyrics
This study introduces a benchtop photon-counting micro-CT system for dynamic small animal perfusion imaging. Deep learning methods enable rapid 5D (3D + Time + Energy) imaging and quantitative blood flow analysis, supporting high-throughput preclinical vascular research.
Allphin AJ, Nadkarni R, Clark DP, Badea CT. Photon-counting micro-CT scanner for deep learning-enabled small animal perfusion imaging. Phys Med Biol. 2025 Jun 27. doi: 10.1088/1361-6560/ade94b. PMID: 40578400
Congratulations! Dr. Hae Sol Moon has successfully defended his PhD on “Integrative Modeling of Alzheimer’s Disease Risk”.
